Study on the Evolution of Urban Spatial and Temporal Patterns in Sichuan Province from the Perspective of Nighttime Light Data

Erli Wang; Xiaofang Liu; Wenzhong Zhu; Yuhao Song; Gonghui Lv; Xiaoqin Deng

doi:10.54691/210sjy44

Authors

Erli Wang
Xiaofang Liu
Wenzhong Zhu
Yuhao Song
Gonghui Lv
Xiaoqin Deng

DOI:

https://doi.org/10.54691/210sjy44

Keywords:

Urban built-up areas, nighttime light, NPP/VIIRS, temporal and spatial evolution, sichuan province.

Abstract

A timely and accurate understanding of spatial-temporal evolution patterns and the development status of cities is essential for effective urban planning. This study utilized NPP/VIIRS nighttime light (NTL) data from 2012 to 2021 to extract the built-up areas of 34 prefecture-level and county-level cities in Sichuan Province. Key indicators, including the urban center of gravity, standard deviation ellipse, expansion speed, expansion intensity, fractal dimension, and compactness, were employed to analyze urban spatial patterns across three stages. The findings reveal that the urban center of gravity in Sichuan Province shifted from northeast to southeast, with cities dispersed in the northwest-southeast direction and clustered in the northeast-southwest direction. Prefecture-level cities generally exhibited high or medium speed to lower development levels, evolving towards relatively low and low intensity expansion, while county-level cities expanded more slowly at low intensity. Furthermore, better-developed cities are primarily located in the eastern region of Sichuan. Throughout the study period, outlying expansion was the predominant urban expansion model, and the spatial evolution of cities demonstrated considerable diversification. This research offers valuable insights into the sustainable development and planning of cities in Sichuan Province.

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References

[1] National Bureau of Statistics, “Statistical bulletin on the national economic and social development of the People’s Republic of China in 2023.” Accessed: Apr. 14, 2024. [Online]. Available: https://www.gov.cn/lianbo/bumen/202402/content_6934935.htm

[2] T. Li, Z. Guo, and C. Ma, “Dynamic characteristics of urbanization based on nighttime light data in China’s ‘Plain–Mountain Transition Zone,’” IJERPH, vol. 19, no. 15, pp. 7–21, 2022.

[3] P. Xu, P. Jin, and Q. Cheng, “Mapping urbanization dynamic of mainland China using DMSP/OLS night time light data,” IOP Conf. Ser.: Earth Environ. Sci., vol. 569, no. 1, pp. 1–14, 2020.

[4] X. Li, L. Zhao, D. Li, and H. Xu, “Mapping urban extent using Luojia 1-01 nighttime light imagery,” Sensors, vol. 18, no. 11, pp. 1–18, 2018.

[5] H. Li and H. Deng, “Progress of extraction of boundaries in urban built-up areas based on multi-source data collaboration,” Geomatics World, vol. 29, no. 4, pp. 81-87+96, 2022.

[6] Q. Wang, Q. Guan, and G. Sun, “Spatio-temporal characteristics of urbanization in Vietnam from a multi-scale perspective: based on night light data,” World Regional Studies, vol. 32, no. 7, pp. 61–74, 2023.

[7] L. Zhang, Z. Ren, B. Chen, P. Gong, B. Xu, and H. Fu, “A prolonged artificial nighttime-light dataset of China (1984-2020),” Sci Data, vol. 11, no. 1, p. 414, 2024.

[8] B. Yu., C. Wang., W. Gong., Z. Chen, K. Shi, B. Wu, et al “Nighttime light remote sensing and urban studies: data, methods, applications, and prospects,” National Remote Sensing Bulletin, vol. 25, no. 1, pp. 342–364, 2021.

[9] N. Levin, C. C.M. Kyba, Q. Zhang, A. S. D. Miguel, M. O. Román, X. Li, et al, “Remote sensing of night lights: a review and an outlook for the future,” Remote Sensing of Environment, vol. 237, no. 19, pp 1-18, 2020.

[10] X. Jing, X. Shao, C. Cao, X. Fu, and L. Yan, “Comparison between the Suomi-NPP Day-Night Band and DMSP-OLS for Correlating Socio-Economic Variables at the Provincial Level in China,” Remote Sensing, vol. 8, no. 1, p. 1-17, 2015.

[11] G. Zhang, X. Guo, D. Li, and B. Jiang, “Evaluating the potential of LJ1-01 nighttime light data for modeling socio-economic parameters,” Sensors (Switzerland), vol. 19, no. 6, pp. 1–13, 2019.

[12] M. Imhoff, W. Lawrence, C. Elvidge, T Paul, E. Levine, M. Privalsky, et al, “Using nighttime DMSP/OLS images of city lights to estimate the impact of urban land use on soil resources in the United States,” Remote Sens Environ, vol. 59, no. 1, pp. 105–117, 1997.

[13] C. He, P. Shi, J. Li, J. Chen, Y. Pan, J. Li, et al, “Research on the spatial process reconstruction of urbanization in Chinese mainland in the 1990s based On DMSP/OLS night light data and statistical data,” Chinese Science Bulletin, vol. 51, no. 7, pp. 856–861, 2006.

[14] S. Shu, B. Yu, J. Wu, and H. Liu, “Methods for deriving urban built-up area using night-light data: assessment and application,” Remote Sensing Technology and Application, vol. 26, no. 2, pp. 169–176, 2011.

[15] M. L.Imhoff, W. T. Lawrence, D. C. Stutzer, and C. D. Elvidge, “A technique for using composite DMSP/OLS ‘city lights’ satellite data to map urban area,” Remote Sensing of Environment, vol. 61, no. 3, pp. 361–370, 1997.

[16] Y. Li, H. Ye, X. Gao, D. Sun, Z. Li, N. Zhang, et al, “Spatiotemporal patterns of urbanization in the three most developed urban agglomerations in China based on continuous nighttime light data (2000–2018),” Remote Sens-basel, vol. 13, no. 12, p. 2245, 2021.

[17] Y. Song, X. Li, G. Tao, and J. Liu, “Exploring the characteristics and drivers of expansion in the Shandong Peninsula Urban Agglomeration based on nighttime light data,” IEEE J-stars, vol. 16, pp. 8535–8549, 2023.

[18] G.Yao, H. LI, J. Wu, N. Wang, and C. Liu, “The coupling coordination degree of ecological environment and urbanization in ecological civilization demonstration area based on remote sensing ecological index and compounded night light index: a case study of the Yangtze River Delta,” Journal of Ecology and Rural Environment, vol. 39, no. 11, pp. 1386–1398, 2023.

[19] L. Zhu and Y. Wang, “Built-up areas extraction method of urban agglomeration in southern Jiangsu based on nighttime light remote sensing image,” Geospatial Information, vol. 21, no. 10, pp. 44–48, 2023.

[20] T. Huang, J. Luo, Z. Gao, and F. Huang, “Evolution of urban spatial pattern of GBA based on DMSP-OLS and LJ-1 nighttime light remote sensing images,” Bulletin of Surveying and Mapping, vol. 12, pp. 10–15, 2021.

[21] Q. Zhi, J. Chen, Y Fu. and B. Guo, “The multi-center spatial structure in the Guangdong-Hong Kong-Macao Greater Bay Area Urban Agglomeration based on luojia1-01 nighttime light data and POI data,” Tropical Geography, vol. 42, no. 3, pp. 444–456, 2022.

[22] Y. Zhang, M. CY, M. Liu, T. Song, and Y. Liu, “Characteristics of temporal and spatial variation of Beijing-Tianjin-Hebei Urban Agglomeration from the perspective of night-light remote sensing,” Journal of North China University of Science and Technology (Natural Science Edition), vol. 45, no. 1, pp. 9–17, 2023.

[23] Y. Li, M. Chen, and Y. Fu, “Analysis of the changes in the Beijing-Tianjin-Hebei urban agglomeration’s spatial structure using NPP-VIIRS data,” Bulletin of Surveying and Mapping, no. 2, pp. 50–55, 2022.

[24] Z Xie., J Shan., and L. Sun, “Main urban district identification method based on multi-source remote sensing images and complex network,” Geomatics & Spatial Information Technology, vol. 46, no. 8, pp. 1–5.

[25] J. Rao, H Ding., and P. Xu, “Extraction of built-up in Shanghai based on Luojia-1,” Jiang Xi Science, vol. 41, no. 2, pp. 261–265, 2023.

[26] B. Tan, “Analysis of the built-up area expansion of Chengdu-Chongqing Urban Agglomeration based on multi-source data,” Chongqing Jiaotong University, Chongqing, 2023.

[27] S. Zheng, “Study on the evolution of the spatial form of Chengdu-Chongqing Urban Agglomeration based on night light remote sensing,” Southwest University of Science and Technology, Mianyang, 2022.

[28] H. Wang., Z. Hu, F. Li, and Y. Zhou, “Research on the Spatial-Temporal Process of Urbanization in Chengdu-Chongqing Region based on Nighttime Light from 2000 to 2018,” Remote Sensing Technology and Application, vol. 37, no. 4, pp. 897–907, 2022.

[29] X. Li, “Spatial morphology evolution analysis of Chengdu city based on luminous remote sensing,” Southwest University of Science and Technology, Mianyang, 2020.

[30] The People’s Government of Sichuan Province, “Administrative Subdivision.” Accessed: Jun. 24, 2024. [Online]. Available: https://www.sc.gov.cn/10462/c112007/2024/3/19/06b6a3f947aa4 19a8dab78d0698893dd.shtml

[31] M. O. Román, Z. Wang, Q. Sun, V. Kalb, SD. Miller, A. Molthan, et al, “NASA’s Black Marble nighttime lights product suite,” Remote Sensing of Environment, vol. 210, pp. 113–143, 2018.

[32] Q.Li, Q.Wu, H. Zhou, B. Zhang, J. Li and L. Lin, “Hefei built-up area extraction based on landsat8 data and ‘Luojia-1’ luminous data,” Anhui Normal University (Natural Science), vol. 44, no. 4, pp. 354–361, 2021.

[33] W. Du, R.Wang, W. Yu, X. Liu, Y. Zhang, and Y. Nian, “Exploring urban expanding pattern of Gansu province using time series of nighttime light remote sensing data,” Remote Sensing Technology and Application, vol. 39, no.3, pp. 659-668, 2024.

[34] Y Liu., “Analysis of urban space expansion characteristics of Hadaqi Industrial Corridor based on night light data,” Beijing Surveying and Mapping, vol. 35, pp. 1191–1195, 2021.